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Scalability Study on Large-scale Parallel Finite element Computing in PANDA Frame

机译:大型平行有限元计算熊猫架的可扩展性研究

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摘要

A Finite-element parallel computing frame - PANDA and its implementation processes are introduced. To validate the parallel performance of the PANDA frame, a series of tests were carried out to obtain the computing scale and the speedup ratios. First, three different large-scale freedom degree models (i.e. 1.83 million, 7 million and 10 million) of a typical engineering clamp were created in MSC. Patran and were translated into geometric-grid files that can be identified in PANDA frame. Second, Linear static parallel computations of the three cases were successfully carried out on large parallel computers with preconditioned conjugate gradient methods in PANDA frame. The speedup ratios of the three cases were obtained with a maximum process number of 64. The results show that the PANDA frame is competent for carrying out large-scale parallel computing of 10 million freedom degrees. In each scale, the parallel computing is nearly linearly accelerated along with the increase of process numbers, moreover, a super-linear speedup appears in some cases. The speedup curves show that the linear degree increases when the computing scale enlarges. The influence of different communication bandwidths on computing efficiency was also discussed. All the testing results indicate that the PANDA frame has excellent parallel performance and favorable computing scalability.
机译:介绍了有限元平行计算框架 - 熊猫及其实现过程。为了验证熊猫帧的并行性能,执行了一系列测试以获得计算规模和加速比率。首先,在MSC中创建了三种不同的大规模自由度模型(即183百万,700万,700万元)。帕特班并被翻译成可以在熊猫框架中识别的几何网格文件。其次,在大型并行计算机上成功地执行三种情况下的线性静态并行计算,其中熊猫框架中的预处理共轭梯度方法。获得三种情况的加速比率为64个。结果表明,熊猫框架是履行大规模平行计算的1000万自由度。在每种规模中,随着过程数量的增加,并行计算几乎线性加速,而且,在某些情况下出现超线性加速。加速曲线表明,当计算规模放大时,线性度会增加。还讨论了不同通信带宽对计算效率的影响。所有测试结果表明,熊猫框架具有出色的并行性能和有利的计算可扩展性。

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